{"title":"通过早期反应评估和方案调整改善结直肠肝转移的治疗:基于临床功能磁共振模型的前瞻性研究。","authors":"Wenhua Li, Huan Zhang, Zhe Gong, Yue Li, Zhiyu Chen, Xiaodong Zhu, Mingzhu Huang, Zhe Zhang, Chenchen Wang, Lixin Qiu, Qirong Geng, Jinjia Chang, Xiaoying Zhao, Xuedan Sheng, Wen Zhang, Tong Tong, Weijian Guo","doi":"10.20892/j.issn.2095-3941.2024.0389","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The aim of the study was to evaluate the feasibility of functional MR in predicting the clinical response to chemotherapy in patients with colorectal liver metastases (CLM).</p><p><strong>Methods: </strong>A total of 196 eligible patients were enrolled in the study between August 2016 and January 2023. Functional MR was performed at baseline and after one cycle of chemotherapy. The diffusion kurtosis radiomic texture features were extracted and a signature model was built using the R package. The initial 100 cases were designated as the training set, the following 48 cases were designated as the validation set, and the final 48 cases were designated as the intervention validation set.</p><p><strong>Results: </strong>Good performance for the response prediction (AUC = 0.818 in the training set and 0.755 in the validation set) was demonstrated. The objective response rates (ORRs) in the high-risk subgroup were significantly lower than the low-risk subgroup in the training and validation sets. Worse progression-free survival and overall survival rates were noted in the high-risk population. In the intervention set 22.9% (11/48) of the chemotherapy regimens for patients were changed in response to the model-predicted results and the ORR reached 77.1% (37/48), which was significantly higher than the training and validation sets [47.97% (71/148); <i>P</i> = 0.000].</p><p><strong>Conclusions: </strong>A functional MR signature effectively predicted the chemotherapy response and long-term survival. The adjustment of the regimen guided by the model significantly improved the ORR.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":5.6000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899590/pdf/","citationCount":"0","resultStr":"{\"title\":\"Improved treatment of colorectal liver metastases by early response evaluation and regimen adjustment: a prospective study of clinical functional MR-based modeling.\",\"authors\":\"Wenhua Li, Huan Zhang, Zhe Gong, Yue Li, Zhiyu Chen, Xiaodong Zhu, Mingzhu Huang, Zhe Zhang, Chenchen Wang, Lixin Qiu, Qirong Geng, Jinjia Chang, Xiaoying Zhao, Xuedan Sheng, Wen Zhang, Tong Tong, Weijian Guo\",\"doi\":\"10.20892/j.issn.2095-3941.2024.0389\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>The aim of the study was to evaluate the feasibility of functional MR in predicting the clinical response to chemotherapy in patients with colorectal liver metastases (CLM).</p><p><strong>Methods: </strong>A total of 196 eligible patients were enrolled in the study between August 2016 and January 2023. Functional MR was performed at baseline and after one cycle of chemotherapy. The diffusion kurtosis radiomic texture features were extracted and a signature model was built using the R package. The initial 100 cases were designated as the training set, the following 48 cases were designated as the validation set, and the final 48 cases were designated as the intervention validation set.</p><p><strong>Results: </strong>Good performance for the response prediction (AUC = 0.818 in the training set and 0.755 in the validation set) was demonstrated. The objective response rates (ORRs) in the high-risk subgroup were significantly lower than the low-risk subgroup in the training and validation sets. Worse progression-free survival and overall survival rates were noted in the high-risk population. In the intervention set 22.9% (11/48) of the chemotherapy regimens for patients were changed in response to the model-predicted results and the ORR reached 77.1% (37/48), which was significantly higher than the training and validation sets [47.97% (71/148); <i>P</i> = 0.000].</p><p><strong>Conclusions: </strong>A functional MR signature effectively predicted the chemotherapy response and long-term survival. The adjustment of the regimen guided by the model significantly improved the ORR.</p>\",\"PeriodicalId\":9611,\"journal\":{\"name\":\"Cancer Biology & Medicine\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2025-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899590/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Biology & Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.20892/j.issn.2095-3941.2024.0389\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Biology & Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.20892/j.issn.2095-3941.2024.0389","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Improved treatment of colorectal liver metastases by early response evaluation and regimen adjustment: a prospective study of clinical functional MR-based modeling.
Objective: The aim of the study was to evaluate the feasibility of functional MR in predicting the clinical response to chemotherapy in patients with colorectal liver metastases (CLM).
Methods: A total of 196 eligible patients were enrolled in the study between August 2016 and January 2023. Functional MR was performed at baseline and after one cycle of chemotherapy. The diffusion kurtosis radiomic texture features were extracted and a signature model was built using the R package. The initial 100 cases were designated as the training set, the following 48 cases were designated as the validation set, and the final 48 cases were designated as the intervention validation set.
Results: Good performance for the response prediction (AUC = 0.818 in the training set and 0.755 in the validation set) was demonstrated. The objective response rates (ORRs) in the high-risk subgroup were significantly lower than the low-risk subgroup in the training and validation sets. Worse progression-free survival and overall survival rates were noted in the high-risk population. In the intervention set 22.9% (11/48) of the chemotherapy regimens for patients were changed in response to the model-predicted results and the ORR reached 77.1% (37/48), which was significantly higher than the training and validation sets [47.97% (71/148); P = 0.000].
Conclusions: A functional MR signature effectively predicted the chemotherapy response and long-term survival. The adjustment of the regimen guided by the model significantly improved the ORR.
期刊介绍:
Cancer Biology & Medicine (ISSN 2095-3941) is a peer-reviewed open-access journal of Chinese Anti-cancer Association (CACA), which is the leading professional society of oncology in China. The journal quarterly provides innovative and significant information on biological basis of cancer, cancer microenvironment, translational cancer research, and all aspects of clinical cancer research. The journal also publishes significant perspectives on indigenous cancer types in China.